diff --git a/experiments/Manifest.toml b/experiments/Manifest.toml
index 48d8a3c8054ee3b28d48e56912552d3f789419ae..4a9e1575bbf958d321c154826335d6f1d28de868 100644
--- a/experiments/Manifest.toml
+++ b/experiments/Manifest.toml
@@ -438,11 +438,11 @@ version = "0.6.3"
[[deps.CounterfactualExplanations]]
deps = ["CSV", "CUDA", "CategoricalArrays", "ChainRulesCore", "DataFrames", "DecisionTree", "Distributions", "EvoTrees", "Flux", "LaplaceRedux", "LazyArtifacts", "LinearAlgebra", "Logging", "MLDatasets", "MLJBase", "MLJDecisionTreeInterface", "MLJModels", "MLUtils", "MultivariateStats", "NearestNeighborModels", "PackageExtensionCompat", "Parameters", "PrecompileTools", "ProgressMeter", "Random", "Serialization", "Statistics", "StatsBase", "Tables", "UUIDs", "cuDNN"]
-git-tree-sha1 = "6ac3b59bcd9d8c75dcbe83822f050247d1143334"
+git-tree-sha1 = "7962ccc6f9e41b3f197b1050e950aca9e3630a18"
repo-rev = "main"
repo-url = "https://github.com/JuliaTrustworthyAI/CounterfactualExplanations.jl.git"
uuid = "2f13d31b-18db-44c1-bc43-ebaf2cff0be0"
-version = "0.1.30"
+version = "0.1.31"
[deps.CounterfactualExplanations.extensions]
MPIExt = "MPI"
diff --git a/experiments/experiment.jl b/experiments/experiment.jl
index a375158e1f71fd22004357cbfd5400a85e40151b..1d733971385ce114eeabbbdb05c081d97f3b37d1 100644
--- a/experiments/experiment.jl
+++ b/experiments/experiment.jl
@@ -9,7 +9,7 @@ Base.@kwdef struct Experiment
use_pretrained::Bool = !RETRAIN
models::Union{Nothing,Dict} = nothing
additional_models::Union{Nothing,Dict} = nothing
- ð’Ÿx::Distribution = Normal()
+ ð’Ÿx::Distribution = ECCCo.prior_sampling_space(counterfactual_data)
sampling_batch_size::Int = 50
sampling_steps::Int = 50
min_batch_size::Int = 128
diff --git a/experiments/grid_search.jl b/experiments/grid_search.jl
index 36904a0815b8dafdc8c17a6ef275966f64eff75e..29ee1982ed25f64eb66e8521f1cdf466187c61fc 100644
--- a/experiments/grid_search.jl
+++ b/experiments/grid_search.jl
@@ -212,10 +212,10 @@ function best_absolute_outcome(
higher_is_better = [var ∈ ["validity", "redundancy"] for var in evaluation.variable]
evaluation.value[higher_is_better] .= -evaluation.value[higher_is_better]
- # Normalise to allow for comparison across measures:
- evaluation =
- groupby(evaluation, [:dataname, :variable]) |>
- x -> transform(x, :value => standardize => :value)
+ # # Normalise to allow for comparison across measures:
+ # evaluation =
+ # groupby(evaluation, [:dataname, :variable]) |>
+ # x -> transform(x, :value => standardize => :value)
# Reconstruct outcome with normalised values:
bmk = CounterfactualExplanations.Evaluation.Benchmark(evaluation)
@@ -239,6 +239,8 @@ function best_absolute_outcome(
params=outcomes[:df_outcomes].params[best_index],
outcome=outcomes[:df_outcomes].outcome[best_index],
)
+
+ return best_outcome
end
best_absolute_outcome_eccco(outcomes; kwrgs...) =
diff --git a/experiments/jobscripts/generators/california_housing.sh b/experiments/jobscripts/generators/california_housing.sh
index 07d5770eceffcd6f892a7b4b0865efa5912da59c..446cb9d9037577894b2763653923d33fa480bc22 100644
--- a/experiments/jobscripts/generators/california_housing.sh
+++ b/experiments/jobscripts/generators/california_housing.sh
@@ -1,14 +1,16 @@
#!/bin/bash
#SBATCH --job-name="California Housing (ECCCo)"
-#SBATCH --time=3:00:00
-#SBATCH --ntasks=100
-#SBATCH --cpus-per-task=1
+#SBATCH --time=00:30:00
+#SBATCH --ntasks=30
+#SBATCH --cpus-per-task=10
#SBATCH --partition=compute
-#SBATCH --mem-per-cpu=8GB
+#SBATCH --mem-per-cpu=4GB
#SBATCH --account=research-eemcs-insy
#SBATCH --mail-type=END # Set mail type to 'END' to receive a mail when the job finishes.
module load 2023r1 openmpi
-srun julia --project=experiments experiments/run_experiments.jl -- data=california_housing output_path=results mpi > experiments/california_housing.log
+source experiments/slurm_header.sh
+
+srun julia --project=experiments --threads $SLURM_CPUS_PER_TASK experiments/run_experiments.jl -- data=california_housing output_path=results mpi threaded n_individuals=100 n_runs=5 > experiments/logs/california_housing.log
diff --git a/experiments/jobscripts/tuning/generators/california_housing.sh b/experiments/jobscripts/tuning/generators/california_housing.sh
index 5e8f4f40818a726489647adf4e8dbac1232189d3..e1805b58d18be6da6c0fb5ddfafdb9086c683fb5 100644
--- a/experiments/jobscripts/tuning/generators/california_housing.sh
+++ b/experiments/jobscripts/tuning/generators/california_housing.sh
@@ -1,7 +1,7 @@
#!/bin/bash
#SBATCH --job-name="Grid-search California Housing (ECCCo)"
-#SBATCH --time=01:30:00
+#SBATCH --time=01:20:00
#SBATCH --ntasks=30
#SBATCH --cpus-per-task=10
#SBATCH --partition=compute
diff --git a/experiments/jobscripts/tuning/generators/gmsc.sh b/experiments/jobscripts/tuning/generators/gmsc.sh
index 9b84593e820aab7f977c7cbbd72905ab65d8b3f0..848b074f9098a633a6a4b9878dffc6e8d53b155c 100644
--- a/experiments/jobscripts/tuning/generators/gmsc.sh
+++ b/experiments/jobscripts/tuning/generators/gmsc.sh
@@ -1,7 +1,7 @@
#!/bin/bash
#SBATCH --job-name="Grid-search GMSC (ECCCo)"
-#SBATCH --time=01:30:00
+#SBATCH --time=01:20:00
#SBATCH --ntasks=30
#SBATCH --cpus-per-task=10
#SBATCH --partition=compute
diff --git a/experiments/utils.jl b/experiments/utils.jl
index be94743d216d6b1ccb07e5094f4a5913ceddeff1..5b77538c3a02dca79bdb8f8d57d4f8bf8f0ba595 100644
--- a/experiments/utils.jl
+++ b/experiments/utils.jl
@@ -1,6 +1,8 @@
using CounterfactualExplanations.Parallelization: ThreadsParallelizer
+using Distributions: Uniform
using Flux
using LinearAlgebra: norm
+using Statistics: mean, std
function is_multi_processed(parallelizer::Union{Nothing,AbstractParallelizer})
if isnothing(parallelizer) || isa(parallelizer, ThreadsParallelizer)
diff --git a/src/sampling.jl b/src/sampling.jl
index aedd495b432947b83bdebc36badb186dfc00ebb7..75776c2c3e85e8a899cebc8fdfc9a0a95a3e033e 100644
--- a/src/sampling.jl
+++ b/src/sampling.jl
@@ -46,8 +46,10 @@ function EnergySampler(
K = length(data.y_levels)
input_size = size(selectdim(data.X, ndims(data.X), 1))
- ð’Ÿx = Uniform(extrema(data.X)...)
+ # Prior distribution:
+ ð’Ÿx = prior_sampling_space(data)
ð’Ÿy = Categorical(ones(K) ./ K)
+ # Sampler:
sampler = ConditionalSampler(ð’Ÿx, ð’Ÿy; input_size = input_size)
yidx = get_target_index(data.y_levels, y)
diff --git a/src/utils.jl b/src/utils.jl
index a476fc6ce73bb39ebdb6db823adbe09e8d3d9c12..a2fae145e9ff47b66929425b47a50e83e9fb4f4f 100644
--- a/src/utils.jl
+++ b/src/utils.jl
@@ -57,3 +57,17 @@ function ssim_dist(x, y)
y = convert2mnist(y)
return (1 - assess_ssim(x, y)) / 2
end
+
+"""
+ prior_sampling_space(data::CounterfactualData; n_std=3)
+
+Define the prior sampling space for the data.
+"""
+function prior_sampling_space(data::CounterfactualData; n_std=3)
+ X = data.X
+ centers = mean(X, dims=2)
+ stds = std(X, dims=2)
+ lower_bound = minimum(centers .- n_std .* stds)[1]
+ upper_bound = maximum(centers .+ n_std .* stds)[1]
+ return Uniform(lower_bound, upper_bound)
+end
\ No newline at end of file